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Homeostatic intrinsic plasticity is often described as an adjustment of neuronal excitability to maintain stable spiking output. Here we report that intrinsic plasticity in the tectum of Xenopus tadpoles also supports temporal tuning, wherein neurons independently adjust spiking responses to fast and slow patterns of synaptic activation. Using the dynamic clamp technique, and five different types of visual, acoustic, and multisensory conditioning, we show that in tadpoles exposed to light flashes, tectal neurons became selective for fast synaptic inputs, while neurons exposed to looming and multisensory stimuli remained responsive to longer inputs. We also report a homeostatic co-tuning between synaptic and intrinsic temporal properties in tectal cells, as neurons that naturally received fast synaptic inputs tended to be most responsive to long-lasting synaptic conductances, and the other way around. These results expand our understanding of plasticity in the brain, and inform future work on the mechanisms of sensorimotor transformation.Significance statementWith the recent explosion of work in neural connectivity reconstruction and biologically inspired deep learning, most researchers concentrate on the topology of connections between neurons, rather than on differences in neuronal tuning. Here we show that in a sensory network in Xenopus tadpoles, different neurons are tuned, and respond stronger, to either short or long synaptic inputs. This tuning tended to be opposite to the actual dynamics of synaptic inputs each cell received, such that neurons that normally receive shorter inputs generated stronger spiking in response to longer testing currents, and the other way around. This observation shows that even in networks that don’t generate oscillations, neurons reshape their temporal selectivity, to optimize their impact on distributed calculations.

Escape behaviors, orienting reflexes, and social behaviors in Xenopus laevis tadpoles have been well-documented in the literature. Schooling behavior experiments allow for the observation of tadpole social interactions and in the past have been used to characterize behavioral deficits in models of neurodevelopmental disorders. Unlike other species of frogs, Xenopus tadpoles show polarized schooling. Not only do tadpoles aggregate, they also swim in the same direction. Quantifying both aggregation and relative swim angle can give us an important measure of social behavior and sensory integration. Past iterations of these experiments have required the continued presence of an experimenter throughout the duration of each trial and relied on expensive software for subsequent data analysis. The instrument configuration and analysis protocol outlined here provide an automated method to assess schooling by delivering a series of timed vibratory stimuli to a group of tadpoles to induce swimming behavior and then controlling a camera to document their positions via still images. Both stimulus delivery and image acquisition are automated using the Python programming language. Analysis is done using ImageJ and custom Python scripts, which are provided in this protocol. The specific equipment configuration and scripts shown here provide one solution, but other equipment and custom scripts can be substituted.

To build a coherent view of the external world, an organism needs to integrate multiple types of sensory information from different sources, a process known as multisensory integration (MSI). Previously, we showed that the temporal dependence of MSI in the optic tectum of Xenopus laevis tadpoles is mediated by the network dynamics of the recruitment of local inhibition by sensory input (Felch et al., 2016). This was one of the first cellular-level mechanisms described for MSI. Here, we expand this cellular level view of MSI by focusing on the principle of inverse effectiveness, another central feature of MSI stating that the amount of multisensory enhancement observed inversely depends on the size of unisensory responses. We show that non-linear summation of crossmodal synaptic responses, mediated by NMDA-type glutamate receptor (NMDARs) activation, form the cellular basis for inverse effectiveness, both at the cellular and behavioral levels. DOI: http://dx.doi.org/10.7554/eLife.25392.001

SummaryThe Xenopus tadpole model offers many advantages for studying molecular, cellular and network mechanisms underlying neurodevelopmental disorders. Essentially every stage of normal neural circuit development, from axon outgrowth and guidance to activity-dependent homeostasis and refinement, has been studied in the frog tadpole, making it an ideal model to determine what happens when any of these stages are compromised. Recently, the tadpole model has been used to explore the mechanisms of epilepsy and autism, and there is mounting evidence to suggest that diseases of the nervous system involve deficits in the most fundamental aspects of nervous system function and development. In this Review, we provide an update on how tadpole models are being used to study three distinct types of neurodevelopmental disorders: diseases caused by exposure to environmental toxicants, epilepsy and seizure disorders, and autism.

The neural circuits in the optic tectum of Xenopus tadpoles are selectively responsive to looming visual stimuli that resemble objects approaching the animal at a collision trajectory. This selectivity is required for adaptive collision avoidance behavior in this species, but its underlying mechanisms are not known. In particular, it is still unclear how the balance between the recurrent spontaneous network activity and the newly arriving sensory flow is set in this structure, and to what degree this balance is important for collision detection. Also, despite the clear indication for the presence of strong recurrent excitation and spontaneous activity, the exact topology of recurrent feedback circuits in the tectum remains elusive. In this study we take advantage of recently published detailed cell-level data from tadpole tectum to build an informed computational model of it, and investigate whether dynamic activation in excitatory recurrent retinotopic networks may on its own underlie collision detection. We consider several possible recurrent connectivity configurations and compare their performance for collision detection under different levels of spontaneous neural activity. We show that even in the absence of inhibition, a retinotopic network of quickly inactivating spiking neurons is naturally selective for looming stimuli, but this selectivity is not robust to neuronal noise, and is sensitive to the balance between direct and recurrent inputs. We also describe how homeostatic modulation of intrinsic properties of individual tectal cells can change selectivity thresholds in this network, and qualitatively verify our predictions in a behavioral experiment in freely swimming tadpoles.

Multisensory integration (MSI) is the process that allows the brain to bind together spatiotemporally congruent inputs from different sensory modalities to produce single salient representations. While the phenomenology of MSI in vertebrate brains is well described, relatively little is known about cellular and synaptic mechanisms underlying this phenomenon. Here we use an isolated brain preparation to describe cellular mechanisms underlying development of MSI between visual and mechanosensory inputs in the optic tectum of Xenopus tadpoles. We find MSI is highly dependent on the temporal interval between crossmodal stimulus pairs. Over a key developmental period, the temporal window for MSI significantly narrows and is selectively tuned to specific interstimulus intervals. These changes in MSI correlate with developmental increases in evoked synaptic inhibition, and inhibitory blockade reverses observed developmental changes in MSI. We propose a model in which development of recurrent inhibition mediates development of temporal aspects of MSI in the tectum. DOI: http://dx.doi.org/10.7554/eLife.15600.001

The functional properties of neural circuits become increasingly robust over development. This allows circuits to optimize their output in response to a variety of input. However, it is not clear whether this optimization is a function of hardwired circuit elements, or whether it requires neural experience to develop. We performed rapidin vivoimaging of calcium signals from bulk-labeled neurons in theXenopus laevisoptic tectum to resolve the rapid spatiotemporal response properties of populations of developing tectal neurons in response to visual stimuli. We found that during a critical time in tectal development, network activity becomes increasingly robust, more correlated, and more synchronous. These developmental changes require normal visual input during development and are disrupted by NMDAR blockade. Our data show that visual activity and NMDAR activation are critical for the maturation of tectal network dynamics during visual system development.

Biophysical properties of neurons become increasingly diverse over development, but mechanisms underlying and constraining this diversity are not fully understood. Here we investigate electrophysiological characteristics of Xenopus tadpole midbrain neurons across development and during homeostatic plasticity induced by patterned visual stimulation. We show that in development tectal neuron properties not only change on average, but also become increasingly diverse. After sensory stimulation, both electrophysiological diversity and functional differentiation of cells are reduced. At the same time, the amount of cross-correlations between cell properties increase after patterned stimulation as a result of homeostatic plasticity. We show that tectal neurons with similar spiking profiles often have strikingly different electrophysiological properties, and demonstrate that changes in intrinsic excitability during development and in response to sensory stimulation are mediated by different underlying mechanisms. Overall, this analysis and the accompanying dataset provide a unique framework for further studies of network maturation in Xenopus tadpoles. DOI: http://dx.doi.org/10.7554/eLife.11351.001, eLife digest Brains consist of many cells called neurons: billions of them in a human brain, and hundreds of thousands in the brain of a small fish or a frog tadpole. Many of these neurons are very much alike, and work together to process information in the brain. Yet while they are similar, they are not exactly identical. One of the reasons for these differences seems to be to allow each neuron to contribute something unique to the overall working of the brain. By looking at how individual neurons within a specific type differ from each other, it is possible to understand more about how they work together. Ciarleglio, Khakhalin et al. have now compared the properties of the neurons in a part of the brain of a developing frog tadpole that processes sensory information. This showed that these neurons appear relatively similar to each other in young tadpoles. However, as the tadpoles grow and their brains become more elaborate the neurons become increasingly diverse, and their properties become more unique and nuanced. One possible explanation is that this diversity reflects new types of neurons being formed; another, that the differences between the neurons reflect how these cells have adapted to different patterns of sensory input they may have experienced. To distinguish between these two possibilities, Ciarleglio, Khakhalin et al. provided a group of older tadpoles with strobe-like visual stimulation and observed that this caused the neurons to become more similar once again. This suggests that neurons can change their response properties to adapt to the type of sensory input they receive, which would allow the animal to better process different types of sensory information. The data collected through these experiments could now be used to build computational models of this part of the tadpole brain. DOI: http://dx.doi.org/10.7554/eLife.11351.002

Experimental behavioral assays and animal models are essential to elucidate the mechanisms that underlie behavioral phenotypes associated with disorders such as Autism Spectrum Disorders and Fragil...